# Fuzzy Similarity based Fuzzy TOPSIS with Multi-distances

### Pasi Luukka, Mario Fedrizzi, Leoncie Niyigena, Mikael Collan

#### Abstract

This article introduces a new extension to fuzzy similarity based fuzzy TOPSIS that uses multi-distance in aggregation. OWA-based multi-distances are used in the aggregation process. For the weight generation in OWA the O'Hagan's method is used to find optimal weights. Several different, predefined orness values were tested. The presented method is applied to a project selection problem.

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#### Paper Citation

#### in Harvard Style

Luukka P., Fedrizzi M., Niyigena L. and Collan M. (2013). **Fuzzy Similarity based Fuzzy TOPSIS with Multi-distances** . In *Proceedings of the 5th International Joint Conference on Computational Intelligence - Volume 1: FCTA, (IJCCI 2013)* ISBN 978-989-8565-77-8, pages 193-200. DOI: 10.5220/0004552601930200

#### in Bibtex Style

@conference{fcta13,

author={Pasi Luukka and Mario Fedrizzi and Leoncie Niyigena and Mikael Collan},

title={Fuzzy Similarity based Fuzzy TOPSIS with Multi-distances},

booktitle={Proceedings of the 5th International Joint Conference on Computational Intelligence - Volume 1: FCTA, (IJCCI 2013)},

year={2013},

pages={193-200},

publisher={SciTePress},

organization={INSTICC},

doi={10.5220/0004552601930200},

isbn={978-989-8565-77-8},

}

#### in EndNote Style

TY - CONF

JO - Proceedings of the 5th International Joint Conference on Computational Intelligence - Volume 1: FCTA, (IJCCI 2013)

TI - Fuzzy Similarity based Fuzzy TOPSIS with Multi-distances

SN - 978-989-8565-77-8

AU - Luukka P.

AU - Fedrizzi M.

AU - Niyigena L.

AU - Collan M.

PY - 2013

SP - 193

EP - 200

DO - 10.5220/0004552601930200